Used Car Price Prediction Using Machine Learning

The increase in new cars and customers' economic inability, global sales of old cars are expanding. As a result, there exists a pressing need for a second-hand automobile method for predicting prices that accurately calculates the value of a car based on number of factors. In the current circumstance, the existing system involves a mechanism in which a seller sets a price at random and the buyer has no knowledge of the car or its value. In fact, the seller doesn't even know the current value of the car or the price at which the car should be sold. To solve this problem, we have developed a very effective model. Regression algorithms are used to provide continuous values as output rather than classified values. This allows for the prediction of the car's real price rather than its price range.